EngAce

EngAce is a cutting-edge, generative AI-powered application revolutionizing Vietnamese English learning. It offers personalized learning experiences combining AI with comprehensive features. The repository contains source code, documentation, and resources for the app.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

Rapid is a web-based modern editor for OpenStreetMap. It integrates advanced mapping tools, authoritative geospatial open data, and cutting-edge technology to empower mappers at all levels to get started quickly, making accurate and fresh edits to maps. Rapid is enhanced with authoritative open data sources and AI-generated roads from the Facebook Map With AI service + buildings from Microsoft open buildings dataset to make adding and editing roads, buildings, and more quick and simple. Rapid also includes data integrity checks to ensure that new map edits are consistent and accurate.

ChatGPT Shortcut is an AI tool designed to maximize efficiency and productivity by providing a concise list of AI instructions. Users can easily find prompts suitable for various scenarios, boosting productivity and work efficiency. The tool offers one-click prompts, optimization for non-English languages, prompt saving and sharing, and a community voting system. It includes a browser extension compatible with Chrome, Edge, Firefox, and other Chromium-based browsers, as well as a Tampermonkey script for custom domain use. The tool is open-source, allowing users to modify the website's nomenclature, usage directives, and prompts for different languages.

TI MINDMAP GPT is an AI-powered tool designed to assist cyber threat intelligence teams in quickly synthesizing and visualizing key information from various Threat Intelligence sources. The tool utilizes Large Language Models (LLMs) to transform lengthy content into concise, actionable summaries, going beyond mere text reduction to provide insightful encapsulations of crucial points and themes. Users can leverage their own LLM keys for personalized and efficient information processing, streamlining data analysis and enabling teams to focus on strategic decision-making.

DataRobot AI Accelerators are code-first workflows to speed up model development, deployment, and time to value using the DataRobot API. The accelerators include approaches for specific business challenges, generative AI, ecosystem integration templates, and advanced ML and API usage. Users can clone the repo, import desired accelerators into notebooks, execute them, learn and modify content to solve their own problems.

CodeProject.AI Server is a standalone, self-hosted, fast, free, and open-source Artificial Intelligence microserver designed for any platform and language. It can be installed locally without the need for off-device or out-of-network data transfer, providing an easy-to-use solution for developers interested in AI programming. The server includes a HTTP REST API server, backend analysis services, and the source code, enabling users to perform various AI tasks locally without relying on external services or cloud computing. Current capabilities include object detection, face detection, scene recognition, sentiment analysis, and more, with ongoing feature expansions planned. The project aims to promote AI development, simplify AI implementation, focus on core use-cases, and leverage the expertise of the developer community.

Azure OpenAI Service provides REST API access to OpenAI's powerful language models including GPT-3, Codex and Embeddings. Users can easily adapt models for content generation, summarization, semantic search, and natural language to code translation. The workshop covers basics, prompt engineering, common NLP tasks, generative tasks, conversational dialog, and learning methods. It guides users to build applications with PowerApp, query SQL data, create data pipelines, and work with proprietary datasets. Target audience includes Power Users, Software Engineers, Data Scientists, and AI architects and Managers.

Dialog is an API-focused tool designed to simplify the deployment of Large Language Models (LLMs) for programmers interested in AI. It allows users to deploy any LLM based on the structure provided by dialog-lib, enabling them to spend less time coding and more time training their models. The tool aims to humanize Retrieval-Augmented Generative Models (RAGs) and offers features for better RAG deployment and maintenance. Dialog requires a knowledge base in CSV format and a prompt configuration in TOML format to function effectively. It provides functionalities for loading data into the database, processing conversations, and connecting to the LLM, with options to customize prompts and parameters. The tool also requires specific environment variables for setup and configuration.

The GraphRAG project is a data pipeline and transformation suite designed to extract meaningful, structured data from unstructured text using LLMs. It enhances LLMs' ability to reason about private data. The repository provides guidance on using knowledge graph memory structures to enhance LLM outputs, with a warning about the potential costs of GraphRAG indexing. It offers contribution guidelines, development resources, and encourages prompt tuning for optimal results. The Responsible AI FAQ addresses GraphRAG's capabilities, intended uses, evaluation metrics, limitations, and operational factors for effective and responsible use.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

AI Hub is a comprehensive solution that leverages artificial intelligence and cloud computing to provide functionalities such as document search and retrieval, call center analytics, image analysis, brand reputation analysis, form analysis, document comparison, and content safety moderation. It integrates various Azure services like Cognitive Search, ChatGPT, Azure Vision Services, and Azure Document Intelligence to offer scalable, extensible, and secure AI-powered capabilities for different use cases and scenarios.

Arch is an intelligent Layer 7 gateway designed to protect, observe, and personalize LLM applications with APIs. It handles tasks like detecting and rejecting jailbreak attempts, calling backend APIs, disaster recovery, and observability. Built on Envoy Proxy, it offers features like function calling, prompt guardrails, traffic management, and standards-based observability. Arch aims to improve the speed, security, and personalization of generative AI applications.

Llama-github is a powerful tool that helps retrieve relevant code snippets, issues, and repository information from GitHub based on queries. It empowers AI agents and developers to solve coding tasks efficiently. With features like intelligent GitHub retrieval, repository pool caching, LLM-powered question analysis, and comprehensive context generation, llama-github excels at providing valuable knowledge context for development needs. It supports asynchronous processing, flexible LLM integration, robust authentication options, and logging/error handling for smooth operations and troubleshooting. The vision is to seamlessly integrate with GitHub for AI-driven development solutions, while the roadmap focuses on empowering LLMs to automatically resolve complex coding tasks.

KDB.AI is a time-based vector database that allows developers to build scalable, reliable, and real-time applications by providing advanced search, recommendation, and personalization for Generative AI applications. It supports multiple index types, distance metrics, top-N and metadata filtered retrieval, as well as Python and REST interfaces. The repository contains samples demonstrating various use-cases such as temporal similarity search, document search, image search, recommendation systems, sentiment analysis, and more. KDB.AI integrates with platforms like ChatGPT, Langchain, and LlamaIndex. The setup steps require Unix terminal, Python 3.8+, and pip installed. Users can install necessary Python packages and run Jupyter notebooks to interact with the samples.

PAIG is an open-source project focused on protecting Generative AI applications by ensuring security, safety, and observability. It offers a versatile framework to address the latest security challenges and integrate point security solutions without rewriting applications. The project aims to provide a secure environment for developing and deploying GenAI applications.

Stellar Chat is a multi-modal chat application that enables users to create custom agents and integrate with local language models and OpenAI models. It provides capabilities for generating images, visual recognition, text-to-speech, and speech-to-text functionalities. Users can engage in multimodal conversations, create custom agents, search messages and conversations, and integrate with various applications for enhanced productivity. The project is part of the '100 Commits' competition, challenging participants to make meaningful commits daily for 100 consecutive days.

ChatGPT is a desktop application available on Mac, Windows, and Linux that provides a powerful AI wrapper experience. It allows users to interact with AI models for various tasks such as generating text, answering questions, and engaging in conversations. The application is designed to be user-friendly and accessible to both beginners and advanced users. ChatGPT aims to enhance the user experience by offering a seamless interface for leveraging AI capabilities in everyday scenarios.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

Open-LLM-VTuber is a voice-interactive AI companion supporting real-time voice conversations and featuring a Live2D avatar. It can run offline on Windows, macOS, and Linux, offering web and desktop client modes. Users can customize appearance and persona, with rich LLM inference, text-to-speech, and speech recognition support. The project is highly customizable, extensible, and actively developed with exciting features planned. It provides privacy with offline mode, persistent chat logs, and various interaction features like voice interruption, touch feedback, Live2D expressions, pet mode, and more.

EngAce is a cutting-edge, generative AI-powered application revolutionizing Vietnamese English learning. It offers personalized learning experiences combining AI with comprehensive features. The repository contains source code, documentation, and resources for the app.

Write Now is an all-in-one writing assistant that helps users elevate their text with features like proofreading, rewriting, friendly and professional tones, concise mode, and custom AI server configuration. It prioritizes user privacy and offers a Lite Edition for trial purposes. Users can install Write Now through the Havoc Store and configure AI server endpoints for enhanced functionality.

LibreOffice AI Content Generator is a simple Python macro script that enables users to generate content from selected words/sentences using OpenAI or Google AI. The script allows users to perform various tasks such as generating content, translating to other languages, summarizing long content, improving content, and custom tasks like solving math questions. It requires APSO, OpenAI API Key, Google AI API Key, zenity for handling progress bars, and specific Python modules. Users need a little knowledge of LibreOffice macros and Python to use this tool effectively.

Obsidian Weaver is a plugin that integrates ChatGPT/GPT-3 into the note-taking workflow of Obsidian. It allows users to easily access AI-generated suggestions and insights within Obsidian, enhancing the writing and brainstorming process. The plugin respects Obsidian's philosophy of storing notes locally, ensuring data security and privacy. Weaver offers features like creating new chat sessions with the AI assistant and receiving instant responses, all within the Obsidian environment. It provides a seamless integration with Obsidian's interface, making the writing process efficient and helping users stay focused. The plugin is constantly being improved with new features and updates to enhance the note-taking experience.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.